The procedure of systematic application of statistical and logical techniques to evaluate and illustrate data is simply known as data analysis. Data is something that plays a vital role in determining the long term robustness of materials in extreme environments as it examines the current models.
There are two main types of data:
- Qualitative Data
- Quantitative Data
What is Quantitative Data?
Quantitative data expresses the value of data in the form of counts and digits; each data set has an exclusive numerical value. It is quantifiable information that can be used for analysis drawn through statistics or to make any sort of mathematical calculations. It is to make real-life decisions based on these derived mathematical calculations. In simple terms, it is inferring real life analysis based on numbers and figures. While qualitative data is less about “how much?” and more about “Why?” quantitative data is all about the prior, i.e. how much? Or how many?
Every day we make use of quantitative information, for example, if you have gone out shopping at Walmart and are looking through the aisle of cereals and dairy products. You point at a box of lucky charms and question how much is it? The worker will reply with the cost of the product. The worker’s answer will collect quantitative data.
Quantitative Data Collection Methods:
Two of the main methods of quantitative data collection methods:
Surveys:
If you look back in time, quantitative methods were restricted to paper based methods and have now made their way onto online mediums. Close-ended questions are generally preferred while collecting data because they let the respondent choose the answer they find most appropriate. This method is better to compare different answers. A Likert scale is mostly used in questionnaires. The reason why surveys are carried out is that it is practically impossible to personally take data from an audience that has way more population than the conventional size.
- Longitudinal Studies
Longitudinal Studies is the type of observational research in which the researcher conducts surveys over a particular time period/ over a substantial course of time. It is carried out for trend analysis, where the chief objective is to analyze and collect a certain pattern in data.
- Cross-sectional Studies
Unlike longitudinal studies, cross-sectional research is carried at a particular period in time across a targeted sample audience. It is carried out to understand the theme from the sample at a specific time.
One-on-one interviews:
Just like questionnaires shifting from paper and physical methods to online methods, one on one interviews has also shifted from face to face interactions to online platforms or telephones. An interview is considered the best method for an interview mainly because it allows the interviewer to collect a lot of data from the interviewee.
- Face to face Interviews
- Telephonic Interviews
- Computer Interviews
What is Qualitative Data?
The type of data which isn’t numerical in nature is qualitative data. It has less to do with numbers. It is mainly collected through different methods of observations, one-on-one interviews, focus groups, etc. In statistics, qualitative data is known as categorical data because it can easily be grouped into categories.
Let’s understand the concept of the word “qualitative” first. Imagine you are part of a speech competition, and there is a panel of judges who will be judging your speech. After you delivered your speech, the judges gave you their feedback on your intonation, the excellence of your content, clear pronunciation and eloquence. All this feedback will come under the umbrella of qualitative because the judgment had more to do with the standard and nature of your speech. If it were to be quantitative, the judges would have given the judgment in the form of numbers.
Qualitative Data Collection Methods:
Unlike quantitative, qualitative data is more in-depth and exploratory in nature. It does not stop at the numbers. It digs deeper into knowing the reasons and why the respondent thinks like that. Qualitative data collection methods are well known:
· Individual Interview
· Qualitative Surveys
· Focus Group Discussions
What is the Significance of Qualitative Data & Quantitative Data?
Qualitative data allows researchers to determine the frequency of qualities. They are allowed to set bounds through which Researchers could observe sets of data. It can help researchers from multiple backgrounds. For example, it can help a business improve their sales by knowing their customers well. They can gather data regarding questions such as where do their customers belong? What are some of the issues they are facing, and what improvements could be made that could help the customers? It deals with the sensitivities of people. Quantitative research is important to gather information about the world we are living in. It produces objective data that can be presented in the form of data and statistics. Quantitative data is mostly collected to measure the impact of a certain event/activity on people. It is very much needed in society to evaluate and examine different situations.
Qualitative vs Quantitative
Qualitative:
There are mainly five methods of Qualitative research, most of which use the same data collection techniques (observation, interviews, etc.); what distinguishes them is the purpose of the research.
Ethnography:
User experience (UX) professionals are more acquainted with this research method. Ethnography literally means “scientific description of people and cultures”. This research method has its origin in social anthropology. Well, qualitative research related to the thesis and you can search the online thesis writing service for your content related to the method. Here, the researchers engross themselves in culture for some time (sometimes for even years) depending on interviews and studies. The researchers engage themselves in the target participants’ environment to have a deeper and clearer understanding of their goals, culture, inspirations, etc.
Narrative:
This particular method knits together experiences, usually from just one person or two individuals, to form a consistent story. Unlike ethnography, it does not come from the firsthand experience of the researcher; it is based on the experiences of other people. You carry out the in-depth interview, and you read long documents. Also if you get any difficulty to write a qualitative research thesis then you will get Phd Thesis Writing Help because if you have short time then you need it. In simple words, you try to demonstrate a larger influence based on the individual story that you are recording. It is not based on a single interview; in fact, interviews are carried out for months, even years. So it can also be said that it’s based on stories that come from individuals. And at the end, the final narrative is formed.
Phenomenological:
A phenomenological study also uses a combination of different methods, including conducting many interviews, going through different documents, and visiting the places and events where the activity is being carried out. It is based on the experience of people who have experienced a specific phenomenon. It covers up to 25 people.
Grounded Theory:
Grounded theory is the method of research where you come up with a theory on the basis of data that has been provided. The essence of an event is being described in this research. A ground theory aims to provide an answer or a theory behind any event. It is primarily done through interviews and documents. The sample size may vary; it is as large as 60 individuals to provide a comprehensive theory.
Case Studies:
A case study, as the name hints, is a very in-depth study of the scenario that is in discussion. It involves a very deep understanding via multiple data sources, i.e. interviews, documents, reports, etc. Thus, cases studies can be both explanatory and exploratory.
Quantitative:
There are many different ways to analyze quantitative data collected in surveys:
Cross-tabulation
The cross-tabulation method has the widest usage. It’s so popular because it uses a basic tabular form to draw interpretations between data sets in the research.
Trend Analysis:
Trend, as the name suggests, is a type of analysis method that observes data for a long period of time. Then, it is used to collect responses about the data changes over the period.
MaxDiff Analysis:
MaxDiff analysis stands for Maximum Difference, which involves the best and worst scales. It is also known as the best-work scaling. In this approach, respondent’s preference scores are recorded for different things. Customer satisfaction and brand preference are surveys where this method of analysis is used. It determines the worst and best-preferred attributes by respondents.
Conjoint Analysis:
Conjoint analysis is somewhat similar to MaxDiff. It carries out an in-depth study to better understand a purchasing decision. Different parameters are set to see what respondents rather prefer.
TURF Analysis:
Turf analysis is used by businesses to get an idea of the market reach of a product or a service and, sometimes, a mix of both. This helps in increasing a business’ performance.
The other methods to analyze quantitative data are Gap analysis, SWOT analysis, and Text Analysis.
Final Words:
This was a concise faceoff between qualitative vs quantitative research. While both methods are prevalent in academic and professional fields, both are very different from one another. With the world moving forward, the importance of data will become more and more significant. Both qualitative and quantitative is important to evaluate situations/scenarios and the reaction of people to them. Taking measures that will bring positive change in the future requires data.
